现代现象学赋予整体作物科学,农学和育种研究的力量
1Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China.
Journal of genetics and genomics = Yi chuan xue bao
|May 11, 2024
概括
农作物现象学使用先进的传感器收集大量的植物数据,加速研究和改善作物育种. 关键的挑战涉及数据标准和农民和育种者的实际现场应用.
科学领域:
- 农业科学 农业科学
- 植物生物学 植物生物学
- 数据科学数据科学数据科学
背景情况:
- 传统的作物测量是耗时且范围有限的.
- 现代作物现象学利用多种传感器进行高通量数据收集.
- 多模式,高维数据捕获植物特征跨空间和时间尺度.
研究的目的:
- 突出作物现象在农业研究中的能力和影响.
- 在作物现象学领域确定当前的挑战和未来的机会.
- 强调现象学在优化作物管理和育种方面的潜力.
主要方法:
- 采用各种传感器 (反射,发射,光) 来获取数据.
- 收集不同空间和时间分辨率的数据.
- 分析多模式,高维数据集.
主要成果:
- 与传统方法相比,作物现象学显著提高了数据收集吞吐量.
- 生成的数据加速了植物生理学,遗传学和系统建模方面的基础研究.
- 现象数据支持优化田间实践,植物工厂和作物育种.
结论:
- 农作物现象学对于推进农业科学和作物改进至关重要.
- 数据收集,管理和处理的标准化是一个很大的机会.
- 为农民和育种者开发实际应用对于直接的农业影响至关重要.
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